A Dynamic Competition Control Strategy for Freeway Merging Region Balancing Individual Behaviour and Traffic Efficiency
An integrated control strategy is considered in this paper with the aim of solving congestion in freeway merging regions during peak hours. Merging regions discussed in this paper include the mainline and on-ramp. Traditional research mainly focuses on the efficiency of traffic, ignoring the experience of on-ramp drivers and passengers. Accordingly, a dynamic competition control strategy is proposed to balance individual behaviour and traffic efficiency. First, the concept of the congestion index is introduced, which is expressed by the queue length and the speed parameter of the merging region. The congestion index is used to balance the priorities of the vehicles from the mainline and on-ramp into the merging region in order to avoid poor individual behaviour of on-ramp drivers due to the long-time waiting. Additionally, a nonlinear optimal control approach integrating variable speed limits control and ramp metering is proposed to minimize the total time spent and the maximum traffic flow. The integrated control approach proposed in this paper is tested by simulation which is calibrated using field data. The results indicate that the integrated control approach can effectively shorten the total delay and enhance the traffic service level.
Zovak G, Kos G, Huzjan B. The Driver Behaviour and Impact of Speed on Road Safety on the Motorways in Croatia. Promet – Traffic&Transportation. 2017;29(2): 155-164. Available from: doi:10.7307/ptt.v29i2.2071
Ziolkowski R. Effectiveness of Automatic Section Speed Control System Operating on National Roads in Poland. Promet – Traffic&Transportation. 2019;31(4): 435-442. Available from: doi:10.7307/ptt.v31i4.3060
Smulders S. Control of freeway traffic flow by variable speed signs. Transportation Research Part B: Methodological. 1990;24(2): 111-132. Available from: doi:10.1016/0191-2615(90)90023-R
Hegyi A, De Schutter B, Hellendoorn J. Optimal coordination of variable speed limits to suppress shock waves. Transportation Research Record. 2003;1852(1): 167-174. Available from: doi:10.3141/1852-21
Hadiuzzaman M, Fang J, Luo Y, et al. Evaluating performance of a proactive optimal variable speed limit control using different objective functions. Procedia-Social and Behavioral Sciences. 2013;96: 2895-2906. Available from: doi:10.1016/j.sbspro.2013.08.321
Li Z, Li Y, Liu P, et al. Development of a variable speed limit strategy to reduce secondary collision risks during inclement weathers. Accident Analysis & Prevention. 2014;72: 134-145. Available from: doi:10.1016/j.aap.2014.06.018
Wang W, Cheng Z. Variable speed limit signs: control and setting locations in freeway work zones. Journal of Advanced Transportation. 2017; 2017. Available from: doi:10.1155/2017/4390630
Kejun L, Meiping Y, Jianlong Z, et al. Model predictive control for variable speed limit in freeway work zone. 2008 27th Chinese Control Conference. IEEE; 2008. p. 488-493.
Heydecker B G, Addison J D. Analysis and modelling of traffic flow under variable speed limits. Transportation Research Part C: Emerging Technologies. 2011; 19(2): 206-217. Available from: doi.org/10.1016/j.trc.2010.05.008
Müller ER, Carlson RC, Kraus W, et al. Microsimulation analysis of practical aspects of traffic control with variable speed limits. IEEE Transactions on Intelligent Transportation Systems. 2015;16(1): 512-523. Available from: doi:10.1109/TITS.2014.2374167
Nissan A, Koutsopoulosb HN. Evaluation of the impact of advisory variable speed limits on motorway capacity and level of service. Procedia-Social and Behavioral Sciences. 2011;16: 100-109. Available from: doi:10.1016/j.sbspro.2011.04.433
Zhao X, Xu W, Ma J, et al. Effects of connected vehicle-based variable speed limit under different foggy conditions based on simulated driving. Accident Analysis & Prevention. 2019;128: 206-216. Available from: doi:10.1016/j.aap.2019.04.020
Soriguera F, Martínez I, Sala M, et al. Effects of low speed limits on freeway traffic flow. Transportation Research Part C: Emerging Technologies. 2017;77: 257-274. Available from: doi:10.1016/j.trc.2017.01.024
Ma M, Yang Q, Liang S, et al. A New Coordinated Control Method on the Intersection of Traffic Region. Discrete Dynamics in Nature and Society. 2016;2016. Available from: doi:10.1155/2016/5985840
Abuamer IM, Celikoglu HB. Local ramp metering strategy ALINEA: Microscopic simulation based evaluation study on Istanbul freeways. Transportation Research Procedia. 2017;22: 598-606. Available from: doi:10.1016/j.trpro.2017.03.050
Hourdakis J, Michalopoulos PG. Evaluation of ramp control effectiveness in two twin cities freeways. Transportation Research Record. 2002;1811(1): 21-29. Available from: doi:10.3141/1811-03
Kotsialos A, Papageorgiou M. Efficiency and equity properties of freeway network-wide ramp metering with AMOC. Transportation Research Part C: Emerging Technologies. 2004;12(6): 401-420. Available from: doi:10.1016/j.trc.2004.07.016
Khoo HL. Dynamic penalty function approach for ramp metering with equity constraints. Journal of King Saud University-Science. 2011;23(3): 273-279. Available from: doi:10.1016/j.jksus.2010.12.004
Yousif S, Al-Obaedi J. Modeling factors influencing the capacity of motorway merge sections controlled by ramp metering. Procedia-Social and Behavioral Sciences. 2011;16: 172-183. Available from: doi:10.1016/j.sbspro.2011.04.440
Tian Q, Huang H-J, Yang H, et al. Efficiency and equity of ramp control and capacity allocation mechanisms in a freeway corridor. Transportation Research Part C.2012;(20): 126-143. Available from: doi:10.1016/j.trc.2011.05.005
Papamichail I, Kotsialos A, Margonis I, et al. Coordinated ramp metering for freeway networks – A model-predictive hierarchical control approach. Transportation Research Part C: Emerging Technologies. 2010;18(3): 311-331. Available from: doi:10.1016/j.trc.2008.11.002
Carlson RC, Papamichail I, Papageorgiou M, et al. Optimal motorway traffic flow control involving variable speed limits and ramp metering. Transportation Science. 2010;44(2): 238-253. Available from: doi:10.1287/trsc.1090.0314
Goatin P, Göttlich S, Kolb O. Speed limit and ramp meter control for traffic flow networks. Engineering Optimization. 2016;48(7): 1121-1144. Available from: doi:10.1080/0305215X.2015.1097099
Papamichail I, Kampitaki K, Papageorgiou M, et al. Integrated ramp metering and variable speed limit control of motorway traffic flow. IFAC Proceedings Volumes. 2008;41(2): 4084-14089. Available from: doi:10.3182/20080706-5-KR-1001.02384
Carlson RC, Papamichail I, Papageorgiou M, et al. Optimal mainstream traffic flow control of large-scale motorway networks. Transportation Research Part C: Emerging Technologies. 2010;18(2): 193-212. Available from: doi:10.1016/j.trc.2009.05.014
Ma M, Liang S. An optimization approach for freeway network coordinated traffic control and route guidance. PloS one. 2018;13(9): e0204255. Available from: doi:10.1371/journal.pone.0204255
Ma M, Liang S. An integrated control method based on the priority of ways in a freeway network. Transactions of the Institute of Measurement and Control. 2018;40(3): 843-852. Available from: doi:10.1177/0142331216668393
Kotsialos A, Papageorgiou M, Diakaki C, et al. Traffic flow modeling of large-scale motorway networks using the macroscopic modeling tool METANET. IEEE Transactions on Intelligent Transportation Systems. 2002;3(4): 282-292. Available from: doi:10.1109/TITS.2002.806804
Sarvi M, Kuwahara M. Using ITS to improve the capacity of freeway merging sections by transferring freight vehicles. IEEE Transactions on Intelligent Transportation Systems. 2008;9(4): 580-588. Available from: doi:10.1109/TITS.2008.2006812
Ossenbruggen PJ. Assessing freeway breakdown and recovery: A stochastic model. Journal of Transportation Engineering. 2016;142(7): 04016025. Available from: doi:10.1061/(ASCE)TE.1943-5436.0000852
Yu R, Abdel-Aty M. An optimal variable speed limits system to ameliorate traffic safety risk. Transportation Research Part C: Emerging Technologies. 2014;46: 235-246. Available from: doi:10.1016/j.trc.2014.05.016
Zhao S, Liang S, Liu H, et al. CTM based real-time queue length estimation at signalized intersection. Mathematical Problems in Engineering. 2015;2015. Available from: doi:10.1155/2015/328712
Ma G, Ma M, Liang S, et al. An improved car-following model accounting for the time-delayed velocity difference and backward looking effect. Communications in Nonlinear Science and Numerical Simulation. 2020; 105221. Available from: doi:10.1016/j.cnsns.2020.105221
Liang S, Ma M, et al. Influence of bus stop location upon traffic flow. Proceedings of the Institution of Civil Engineers-Municipal Engineer. 2019;04. Available from: doi:10.1680/jmuen.18.00059
Hegyi A, De Schutter B, Hellendoorn H. Model predictive control for optimal coordination of ramp metering and variable speed limits. Transportation Research Part C: Emerging Technologies. 2005;13(3): 185-209. Available from: doi:10.1016/j.trc.2004.08.001
Copyright (c) 2020 Minghui Ma, Shidong Liang, Hu Zhang
This work is licensed under a Creative Commons Attribution 4.0 International License.
Authors who publish with this journal agree to the following terms:
- Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.
- Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.
- Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See The Effect of Open Access).